I leverage my training in physics, mathematics and
computing to create educational environments and content that may be utilized in and out of
school settings to facilitate learning physics and math concepts.

I explore a point of view about knowing and learning called situated cognition.
This point of view emphasizes the centrality, in cognition and idea formation, of the environment within which learners experience and conceptualize information.

My math and science class curricula and practices aim to maintain the real-world physical complexity of concepts and phenomena.
Maintaining the natural complexity of the learning environment helps learners transfer their knowledge and apply their ideas when faced with real-world tasks.
Real-world applications of physical principles often involve using approximation techniques. These techniques are important as
an understanding of approximations and corrections is needed when a complex environment is modelled by principles of physics which accurately describe perfectly controlled settings.

For example, the flight of a baseball, football or basketball under ideal conditions (no forces due to air-resistance, in a non-rotating world etc.) would be described by a perfect parabolic arc.
In the real-world however we have to correct for air-resistance for example, which depends on the shape and size of the ball for one. Classroom and lab experiments often seem to "fail" discouragingly,
when a fruitful discussion opportunity might arise if the experiment or situation were to be representative of real-world complexity.

In my classroom and extra-curricular practices I also attempt to enhance the scope and size of
student discussion and working groups carrying out experiments and projects,
by facilitating inter-group and intra-group communication.
Discussing concepts and problems in structured social groups often makes learning more efficient by
sharing the "frustration load" and allowing individual strengths to contribute meaningfully to
group tasks. It also creates more fruitful dialogue and discussion, especially when choosing appropriate
approximations in modelling real-world complexity.